Named entity recognitionSpan-based methodsSemantic dependencySpan-based methods for nested named entity recognition (NER) are effective in handling the complexities of nested entities with hierarchical structures. However, these methods often overlook valid semantic dependencies among global spans, resulting ...
1)基于超图的方法(hypergraph-based)使用显式超图来表示可能的嵌套结构或研究图形的词汇/句法特征;2)基于分层的方法(layered-based)通过动作序列或分层模型构建嵌套结构 ;3)基于span的方法(span-based)直接枚举句子中的span,并对每个span进行分类预测。基于span的方法采用最简单直接的形式作为span分类,因此最近在联合关系...
[4]Xia, Congying, et al. "Multi-Grained Named Entity Recognition."arXiv preprint arXiv:1906.08449(2019). [5]Fisher, Joseph, and Andreas Vlachos. "Merge and Label: A novel neural network architecture for nested NER."arXiv preprint arXiv:1907.00464(2019). [6]Lin, Hongyu, et al. "Sequen...
References [1] Nested Named Entity Recognition Revisited [1] Straková, Jana, Milan Straka, and Jan Hajič. "Neural architectures for nested NER through linearization." arXiv preprint arXiv:1908.06926 (2019). [2] Straková, Jana, Milan Straka, and Jan Hajič. "Neural architectures for ne...
Named entity recognition (NER) is a fundamental problem in natural language processing. In particular, nested entities are commonly existed in real-life textual data for the NER task. However, the current span-based methods for nested NER are computationally expensive, lacking of explicit boundary ...
Span-based modelMulti-task learningNamed Entity Recognition (NER) is generally regarded as a sequence labeling task, which faces a serious problem when the named entities are nested. In this paper, we propose a span-based model for nested NER, which enumerates all possible spans as potential ...
nested named entity recognitionspan classificationprototypegraph attention networkNamed entity recognition, a fundamental task in natural language processing, faces challenges related to the sequence labeling framework widely used when dealing with nested entities. The span-based method transforms nested named ...
Nested Named Entity RecognitionSequence LabelingSpan ClassificationContrastive LearningMulti-Task LearningIn Natural Language Processing (NLP), it is common for one entity to contain another entity, i.e., nested entities. However, the most commonly used methods can only handle flat entities but not ...
命名实体识别是将给定文本中的文本片段(span)识别出来并进行分类。 过去的命名实体识别主要考虑的是扁平命名实体识别(flat NER)。近年来有一些工作考虑了实体之间可能存在嵌套关系,由此对应地提出嵌套命名实体识别(nested NER)这一新任务。 具体来说,如下图(1)所示:“上海市红十字会”就是一个典型的包含嵌套命名实体...
part-of-speech嵌入 0.1 总结 主要用span解决了nested named entity的问题,具体来说就是枚举左右边界,然后再对左右边界做回归运算,从而达到精细调整的目的。 自定义参数实在太多,想去找一下代码,结果没找到。。 发布于 2022-02-11 21:37 ACL 2021 NER ...